Unmanned aerial vehicle path optimization method based on chaotic mapping pelican optimization algorithm

The invention discloses an unmanned aerial vehicle path optimization method based on a chaotic mapping pelican optimization algorithm, and the method comprises the steps: firstly inputting map model parameters, simulating a mountain range environment, building a three-dimensional environment map, inputting the information of an unmanned aerial vehicle path optimization problem, and constructing a multi-objective function; according to the improved pelicans optimization algorithm, the algorithm parameter population number N and the maximum iteration number T are determined, an initialized population is generated through Logistic chaotic mapping, and the fitness is calculated; in the algorithm development stage, when pelicans approach a prey, a prey generation formula is introduced to generate the position of the prey, adaptive search and Levy flight strategies are embedded, and the positions of population individuals in different dimensions in the development stage are updated; in an algorithm local exploratio